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Detecting errors in data: clarification of the impact of base rate expectations and incentives

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  • Klein, Barbara D.

Abstract

Organizational databases have a significant rate of data errors and detecting and correcting these errors can be problematic. This paper builds on a stream of research demonstrating that users of these databases can detect data errors under certain circumstances. A theory of error detection and research on the effect of base rate expectations in probabilistic judgement tasks are applied to the development of two propositions about error detection. It is argued that expectations about the base rate of errors in data affect error detection performance when they are developed through direct experience and that incentives affect error detection performance. The two research propositions are tested in a laboratory experiment. Experience-based expectations about the base rate of errors and incentives are found to affect error detection performance.

Suggested Citation

  • Klein, Barbara D., 2001. "Detecting errors in data: clarification of the impact of base rate expectations and incentives," Omega, Elsevier, vol. 29(5), pages 391-404, October.
    • Handle: RePEc:eee:jomega:v:29:y:2001:i:5:p:391-404
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    References listed on IDEAS

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    2. Stephan Leitner, 2014. "A simulation analysis of interactions among intended biases in costing systems and their effects on the accuracy of decision-influencing information," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(1), pages 113-138, March.
    3. Sundararaghavan, P.S. & Kunnathur, Anand & Fang, Xiao, 2010. "Sequencing questions to ferret out terrorists: Models and heuristics," Omega, Elsevier, vol. 38(1-2), pages 12-19, February.

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